Traditional information technology (IT) architecture have relied on centralized computing structures, whereby all or most of the processing and computing is performed on a central server. Centralized computing can enable the deployment of central server computing resources, administration, and management. Typically, computational processing involves the extraction, transformation and loading of a resultant data feeds by the centralized computing structure.
However, cost and performance inefficiencies of centralized computing structures have steered IT architectures towards decentralized computing structures, whereby data feeds are extracted, uploaded to a decentralized computing platform and then transformed. Doing so provides cost and performance efficiencies since the infrastructure to perform the computational processing can be outsourced to an entity that specializes in such.
As decentralized computing develops, both the velocity and diversity of data can cause some security measures to have an impact on latency, scalability, and recovery performance. Thus, security can be viewed as a service constraint. Thus there is a need to balance security constraints with other competing service constraints when optimizing operation requirements of a platform.